#FactCheck: Old Salman Khan Video From 2019 Misleadingly Shared as Eid Post

Executive Summary:

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A viral video circulating on social media shows a man attempting to fly using a helicopter like fan attached to his body, followed by a crash onto a parked car. The clip was widely shared with humorous captions, suggesting it depicts a real life incident. Given the unusual nature of the visuals, the video was subjected to technical verification using AI content detection tools. Analysis using the AI detection platform indicates that the video is AI generated, and not a genuine real world event.

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Claim:

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A viral video (archive link) claims to show a person attempting to fly using a self made helicopter fan mechanism, briefly lifting off before crashing onto a car in a public setting. The video shows a man attempting to fly by strapping a helicopter like rotating fan to himself, essentially trying to imitate a human helicopter using a DIY mechanism. For a brief moment, it appears as if the device might work, but the attempt quickly fails due to lack of control, engineering support, and safety measures. Within seconds, the man loses balance and crashes down, landing on top of a parked car. The scene highlights a mix of overconfidence, unregulated experimentation, and risk taking carried out in a public space, with bystanders watching rather than intervening. The clip is shared humorously with the caption “India is not for beginners”.

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Fact Check:

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To verify the authenticity of the video, it was analyzed using the Hive Moderation AI detection tool, a widely used platform for identifying synthetic and AI generated media. The tool flagged the video with a high probability of AI generation, indicating that the visuals are not captured from a real physical event. Additional indicators such as unrealistic motion physics, inconsistent human object interaction further support the conclusion that the clip was artificially generated or heavily manipulated using generative AI techniques. No credible news reports or independent eyewitness sources corroborate the occurrence of such an incident.

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Conclusion:

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The claim that the video shows an individual attempting and failing to fly using a helicopter like device is false. Technical analysis confirms that the video is AI generated, and it should be treated as synthetic or fictional content rather than a real life incident. This case highlights how AI generated videos, when shared without context, can mislead audiences and be mistaken for real events, reinforcing the need for verification tools and critical evaluation of viral content.

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• Claim: A viral video claims to show a person attempting to fly using a self made helicopter fan mechanism, briefly lifting off before crashing onto a car in a public setting
• Claimed On: X (Formally Twitter)
• Fact Check: False and Misleading

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Introduction

Digital Public Infrastructure (DPI) serves as the backbone of e-governance, enabling governments to deliver services more efficiently, transparently, and inclusively. By leveraging information and communication technology (ICT), digital governance systems reconfigure traditional administrative processes, making them more accessible and citizen-centric. However, the successful implementation of such systems hinges on overcoming several challenges, from ensuring data security to fostering digital literacy and addressing infrastructural gaps.

This article delves into the key enablers that drive effective DPI and outlines the measures already undertaken by the government to enhance its functionality. Furthermore, it outlines strategies for their enhancement, emphasizing the need for a collaborative, secure, and adaptive approach to building robust e-governance systems.

Key Enablers of DPI

Digital Public Infrastructure (DPI), the foundation for e-governance,  relies on common design, robust governance, and private sector participation for efficiency and inclusivity. This requires common principles, frameworks for collaboration, capacity building, and the development of common standards. Some of the key measures undertaken by the government in this regard include: 

1. Data Protection Framework: The Digital Personal Data Protection (DPDP) Act of 2023 establishes a framework to ensure consent-based data sharing and regulate the processing of digital personal data. It delineates the responsibilities of data fiduciaries in safeguarding users' digital personal data.
2. Increasing Public-Private Partnerships: Refining collaboration between the government and the private sector has accelerated the development, maintenance, expansion, and trust of the infrastructure of DPIs, such as the AADHAR, UPI, and  Data Empowerment and Protection Architecture (DEPA). For example, the Asian Development Bank attributes the success of UPI to its “consortium ownership structure”, which enables the wide participation of major financial stakeholders in the country.
3. Coordinated Planning: The PM-Gati Shakti establishes a clear coordination framework involving various inter-governmental stakeholders at the state and union levels. This aims to significantly reduce project duplications, delays, and cost escalations by streamlining communication, harmonizing project appraisal and approval processes, and providing a comprehensive database of major infrastructure projects in the country. This database called the National Master Plan, is jointly accessible by various government stakeholders through APIs.
4. Capacity Building for Government Employees:  The National e-Governance Division of the Ministry of Electronics and Information Technology routinely rolls out multiple training programs to build the technological and managerial skills required by government employees to manage Digital Public Goods (DPGs). For instance, it recently held a program on “Managing Large Digital Transformative Projects”. Additionally, the Ministry of Personnel, Public Grievances, and Pensions has launched the Integrated Government Online Training platform  (iGOT) Karmayogi for the continuous learning of civil servants across various domains. 

Digital Governance; Way Forward

E-governance utilizes information and communication technology (ICT) such as Wide Area Networks, the Internet, and mobile computing to implement existing government activities, reconfiguring the structures and processes of governance systems. This warrants addressing certain inter-related challenges such as : 

1. Data Security: The dynamic and ever-changing landscape of cyber threats necessitates regular advancements in data and information security technologies, policy frameworks, and legal provisions. Consequently, the digital public ecosystem must incorporate robust data cybersecurity measures, advanced encryption technologies, and stringent privacy compliance standards to safeguard against data breaches.
2. Creating Feedback Loops: Regular feedback surveys will help government agencies improve the quality, efficiency, and accessibility of digital governance services by tailoring them to be more user-friendly and enhancing administrative design. This is necessary to build trust in government services and improve their uptake among beneficiaries. Conducting the decennial census is essential to gather updated data that can serve as a foundation for more informed and effective decision-making.
3. Capacity Building for End-Users: The beneficiaries of key e-governance projects like Aadhar and UPI may have inadequate technological skills, especially in regions with weak internet network infrastructure like hilly or rural areas. This can present challenges in the access to and usage of technological solutions.  Robust capacity-building campaigns for beneficiaries can provide an impetus to the digital inclusion efforts of the government.
4. Increasing the Availability of Real-Time Data: By prioritizing the availability of up-to-date information, governments and third-party enterprises can enable quick and informed decision-making.  They can effectively track service usage, assess quality, and monitor key metrics by leveraging real-time data. This approach is essential for enhancing operational efficiency and delivering improved user experience.
5. Resistance to Change: Any resistance among beneficiaries or government employees to adopt digital governance goods may stem from a limited understanding of digital processes and a lack of experience with transitioning from legacy systems.  Hand-holding employees during the transitionary phase can help create more trust in the process and strengthen the new systems. 

Conclusion

Digital governance is crucial to transforming public services, ensuring transparency, and fostering inclusivity in a rapidly digitizing world. The successful implementation of such projects requires addressing challenges like data security, skill gaps, infrastructural limitations, feedback mechanisms, and resistance to change. Addressing these challenges with a strategic, multi-stakeholder approach can ensure the successful execution and long-term impact of large digital governance projects. By adopting robust cybersecurity frameworks, fostering public-private partnerships, and emphasizing capacity building, governments can create efficient and resilient systems that are user-centric, secure, and accessible to all. 

References

• https://www.adb.org/sites/default/files/publication/865106/adbi-wp1363.pdf 
• https://www.jotform.com/blog/government-digital-transformation-challenges/ 
• https://aapti.in/wp-content/uploads/2024/06/AaptixONI-DPIGovernancePlaybook_compressed.pdf 
• https://community.nasscom.in/sites/default/files/publicreport/Digital%20Public%20Infrastructure%2022-2-2024_compressed.pdf 
• https://proteantech.in/articles/Decoding-Digital-Public-Infrastructure-in-India/ 

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The World Economic Forum reported that AI-generated misinformation and disinformation are the second most likely threat to present a material crisis on a global scale in 2024 at 53% (Sept. 2023). Artificial intelligence is automating the creation of fake news at a rate disproportionate to its fact-checking. It is spurring an explosion of web content mimicking factual articles that instead disseminate false information about grave themes such as elections, wars and natural disasters. 

According to a report by the Centre for the Study of Democratic Institutions, a Canadian think tank, the most prevalent effect of Generative AI is the ability to flood the information ecosystem with misleading and factually-incorrect content. As reported by Democracy Reporting International during the 2024 elections of the European Union, Google's Gemini, OpenAI’s ChatGPT 3.5 and 4.0, and Microsoft’s AI interface ‘CoPilot’ were inaccurate one-third of the time when engaged for any queries regarding the election data.   Therefore, a need for an innovative regulatory approach like regulatory sandboxes which can address these challenges while encouraging responsible AI innovation is desired.

What Is AI-driven Misinformation?

False or misleading information created, amplified, or spread using artificial intelligence technologies is AI-driven misinformation. Machine learning models are leveraged to automate and scale the creation of false and deceptive content. Some examples are deep fakes, AI-generated news articles, and bots that amplify false narratives on social media.

The biggest challenge is in the detection and management of AI-driven misinformation. It is difficult to distinguish AI-generated content from authentic content, especially as these technologies advance rapidly. 

AI-driven misinformation can influence elections, public health, and social stability by spreading false or misleading information. While public adoption of the technology has undoubtedly been rapid, it is yet to achieve true acceptance and actually fulfill its potential in a positive manner because there is widespread cynicism about the technology - and rightly so. The general public sentiment about AI is laced with concern and doubt regarding the technology’s trustworthiness, mainly due to the absence of a regulatory framework maturing on par with the technological development. 

Regulatory Sandboxes: An Overview

Regulatory sandboxes refer to regulatory tools that allow businesses to test and experiment with innovative products, services or businesses under the supervision of a regulator for a limited period. They engage by creating a controlled environment where regulators allow businesses to test new technologies or business models with relaxed regulations.

Regulatory sandboxes have been in use for many industries and the most recent example is their use in sectors like fintech, such as the UK’s Financial Conduct Authority sandbox. These models have been known to encourage innovation while allowing regulators to understand emerging risks. Lessons from the fintech sector show that the benefits of regulatory sandboxes include facilitating firm financing and market entry and increasing speed-to-market by reducing administrative and transaction costs. For regulators, testing in sandboxes informs policy-making and regulatory processes. Looking at the success in the fintech industry, regulatory sandboxes could be adapted to AI, particularly for overseeing technologies that have the potential to generate or spread misinformation.

The Role of Regulatory Sandboxes in Addressing AI Misinformation

Regulatory sandboxes can be used to test AI tools designed to identify or flag misinformation without the risks associated with immediate, wide-scale implementation. Stakeholders like AI developers, social media platforms, and regulators work in collaboration within the sandbox to refine the detection algorithms and evaluate their effectiveness as content moderation tools.

These sandboxes can help balance the need for innovation in AI and the necessity of protecting the public from harmful misinformation. They allow the creation of a flexible and adaptive framework capable of evolving with technological advancements and fostering transparency between AI developers and regulators. This would lead to more informed policymaking and building public trust in AI applications.

CyberPeace Policy Recommendations 

Regulatory sandboxes offer a mechanism to predict solutions that will help to regulate the misinformation that AI tech creates. Some policy recommendations are as follows: 

1. Create guidelines for a global standard for including regulatory sandboxes that can be adapted locally and are useful in ensuring consistency in tackling AI-driven misinformation.
2. Regulators can propose to offer incentives to companies that participate in sandboxes. This would encourage innovation in developing anti-misinformation tools, which could include tax breaks or grants.
3. Awareness campaigns can help in educating the public about the risks of AI-driven misinformation and the role of regulatory sandboxes can help manage public expectations.
4. Periodic and regular reviews and updates to the sandbox frameworks should be conducted to keep pace with advancements in AI technology and emerging forms of misinformation should be emphasized.

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Conclusion and the Challenges for Regulatory Frameworks

Regulatory sandboxes offer a promising pathway to counter the challenges that AI-driven misinformation poses while fostering innovation. By providing a controlled environment for testing new AI tools, these sandboxes can help refine technologies aimed at detecting and mitigating false information. This approach ensures that AI development aligns with societal needs and regulatory standards, fostering greater trust and transparency. With the right support and ongoing adaptations, regulatory sandboxes can become vital in countering the spread of AI-generated misinformation, paving the way for a more secure and informed digital ecosystem.

References

• https://www.thehindu.com/sci-tech/technology/on-the-importance-of-regulatory-sandboxes-in-artificial-intelligence/article68176084.ece
• https://www.oecd.org/en/publications/regulatory-sandboxes-in-artificial-intelligence_8f80a0e6-en.html
• https://www.weforum.org/publications/global-risks-report-2024/
• https://democracy-reporting.org/en/office/global/publications/chatbot-audit#Conclusions

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